Code from BasicOptimizer.scala:75 executed in 39.73 seconds (0.830 gc):

    val lineSearchInstance: LineSearchStrategy = lineSearchFactory
    IterativeTrainer.wrap(trainable)
      .setOrientation(orientation())
      .setMonitor(new TrainingMonitor() {
        override def clear(): Unit = trainingMonitor.clear()
  
        override def log(msg: String): Unit = trainingMonitor.log(msg)
  
        override def onStepFail(currentPoint: Step): Boolean = {
          BasicOptimizer.this.onStepFail(trainable, currentPoint)
        }
  
        override def onStepComplete(currentPoint: Step): Unit = {
          if (0 < logEvery && (0 == currentPoint.iteration % logEvery || currentPoint.iteration < logEvery)) {
            val image = currentImage
            timelineAnimation += image
            val caption = "Iteration " + currentPoint.iteration
            out.p(caption + "\n" + out.jpg(image, caption))
          }
          BasicOptimizer.this.onStepComplete(trainable, currentPoint)
          trainingMonitor.onStepComplete(currentPoint)
          super.onStepComplete(currentPoint)
        }
      })
      .setTimeout(trainingMinutes, TimeUnit.MINUTES)
      .setMaxIterations(trainingIterations)
      .setLineSearchFactory((_: CharSequence) => lineSearchInstance)
      .setTerminateThreshold(java.lang.Double.NEGATIVE_INFINITY)
      .runAndFree
      .asInstanceOf[lang.Double]

Logging:

    Reset training subject: 915095263456200
    Reset training subject: 915095972890700
    Adding measurement 463be8bd to history. Total: 0
    LBFGS Accumulation History: 1 points
    Constructing line search parameters: GD+Trust
    th(0)=0.6596541404724121;dx=-1.259612907998424E-7
    Armijo: th(2.154434690031884)=0.6596541404724121; dx=-1.2596128609241972E-7 evalInputDelta=0.0
    Armijo: th(1.077217345015942)=0.6596541404724121; dx=-1.2596129180506315E-7 evalInputDelta=0.0
    Armijo: th(0.3590724483386473)=0.6596541404724121; dx=-1.2596129070276597E-7 evalInputDelta=0.0
    Armijo: th(0.08976811208466183)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.017953622416932366)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002992270402822061)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(4.2746720040315154E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.0017098688016126062)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.001068668001007879)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(7.480676007055152E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(5.877674005543334E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(5.076173004787425E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(4.67542250440947E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(4.475047254220493E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(4.374859629126004E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(4.4249534416732485E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(4.399906535399626E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(4.4124299885364373E-4)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    W

...skipping 1886 bytes...

    tDelta=0.0
    Armijo: th(0.0023736549516991607)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0021362894565292445)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.0022549722041142026)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0021956308303217233)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.0022253015172179627)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002210466173769843)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0022030485020457834)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002206757337907813)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002204902919976798)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002203975711011291)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    Armijo: th(0.002203512106528537)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0022032803042871603)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0022033962054078485)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.002203454155968193)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.002203483131248365)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    WOLFE (weak): th(0.0022034976188884513)=0.6596541404724121; dx=-1.259612907998424E-7 evalInputDelta=0.0
    mu ~= nu (0.0022034976188884513): th(0.0)=0.6596541404724121
    Fitness changed from 0.6596541404724121 to 0.6596541404724121
    Static Iteration Total: 16.8557; Orientation: 0.0072; Line Search: 15.4952
    Iteration 2 failed. Error: 0.6596541404724121
    Previous Error: 0.0 -> 0.6596541404724121
    Optimization terminated 2
    Final threshold in iteration 2: 0.6596541404724121 (> -Infinity) after 39.734s (< 720.000s)
    

Returns:

    0.6596541404724121